Category Archives: Uncategorized

Abstract-This research examines the impact of artificial intelligence (AI) and machine learning (ML) on improving human resource (HR) decision-making procedures, with an emphasis on the years from 2015 to 2025. Employing a bibliometric approach, the study uncovers trends, obstacles, and prospects related to artificial intelligence and machine learning usage in human resource management. The results depicted in Figure 1 (“Document by Year”) indicate a marked rise in research activity after 2020, emphasizing an increasing interest in the incorporation of AI and ML in HR practices. Figure 2 (“Document by Area”) illustrates that computer science (45%) and business studies (30%) lead in research contributions, highlighting the technical and strategic aspects of these technologies. The geographic analysis shown in Figure 5 (“Document by Country”) reveals that 40% of the studies come from the United States, while European and Asian nations account for 30% and 20%, respectively. Institutional contributions, shown in Figure 7 (“Document by Affiliation”), indicate that 60% of research originates from academic institutions, while corporate research centers account for 25%. Figures 3 and 4 underscore the variety of sources and funding, showing a balance between academic integrity and practical uses, with government funding representing 50%. The research highlights the revolutionary impact of Artificial intelligence and Machine learning in human resource management, especially concerning talent acquisition, employee engagement, and workforce management. Nevertheless, ethical issues, biases in algorithms, and privacy threats present significant challenges. By combining technological advancements with ethical guidance, as illustrated by the trends shown in the figures, organizations can develop adaptable, inclusive, and effective HR systems that meet the changing needs of the workforce.

Abstract-Heart attacks remain a critical global health issue, necessitating accurate predictive models to identify at- risk individuals and support preventive care. This project, titled “Heart Attack Risk Assessment Using Deep Learning with Feature Optimization,” applies deep learning techniques to assess the likelihood of a heart attack. The study utilizes a Fully Connected Neural Network (FCNN) model enhanced by feature optimization methods, ensuring that the most relevant predictors are prioritized. Additionally, the project incorporates risk visualization, enabling clear and actionable insights for early detection and management of heart attack risks.

Abstract-This journal discuss in detail on a suggested medication reminder device that will be made for senior citizens based on their problems. This study’s background is explained in the report, and its primary goal is to guarantee that the medication reminder device will be resolving issues that older people have. The problems that have been discovered are mostly focused at the elderly and are meant to address the problems that they encounter on a daily basis, particularly with regard to medication use. In order to design a better device, the study will also examine similar implemented devices and systems to determine the advantages and disadvantages of other pertinent devices and systems. This portable and economical system would be helpful to every age group also.

Abstract-Microglia, the principal immune cells within the central nervous system (CNS), are essential for maintaining neuronal homeostasis. Nonetheless, the chronic activation of microglia has been associated with the development of neurodegenerative diseases, notably Alzheimer’s Disease (AD) and Parkinson’s Disease (PD). This review investigates the mechanisms underlying microglial activation, the dual functions of microglia in neuroprotection and neurotoxicity, and the implications for therapeutic strategies. By examining contemporary research, we aim to clarify the molecular pathways that link microglial activation to the progression of these diseases and identify potential approaches for modulating microglial responses to alleviate neurodegeneration.

Abstract-Mechanical engineers dream up and design amazing machines and technologies that improve people’s lives in all kinds of ways. From airplanes and cars to robots and renewable energy systems, mechanical engineers have shaped our modern world. New technologies are opening up incredible opportunities for innovation. Read on to learn about the exciting changes & future trends in mechanical engineering and how you can prepare for it!

Abstract-This paper aims to provide an in-depth understanding of A.I., its historical development, and its transformative influence on modern civilisation. We will discuss significant concepts, evolving technologies under influence, technological advancements, and ethical and unethical A.I..

Abstract-Facial expression detection has emerged as a transformative technology with applications in numerous fields such as healthcare, security, and entertainment. The proposed system aims to enhance user engagement by dynamically tailoring playlists based on the user’s emotional state. The proposed Emotion Recognition provides a foundation for further exploration and development of intelligent systems that adapt to users’ emotional states, fostering more immersive and personalized interactions in the realm of digital entertainment.

Abstract-This research introduces two innovative methods to convert a standard 16-control dental chair into an IoT-enabled dental chair at a minimal cost of under 2,000 INR. The first method involves directly interfacing the chair’s control wires with a 16-channel relay and an ESP32 microcontroller, enabling remote operation through the Blynk IoT platform. The second method leverages signal analysis by identifying the dental chair PCB’s communication lines, capturing control signals with a logic analyzer, and replicating them via the ESP32 for seamless functionality. Both approaches offer global control with minimal delay (<10ms) and enhance operational efficiency by enabling preemptive actions, such as heating water or cleaning the spit bowl remotely. This study provides a scalable, low-cost solution for modernizing dental chairs, ensuring ease of use and adaptability for dental clinics worldwide.

Abstract-One of the important and tedious tasks in agricultural practices is the detection of disease on crops. It requires time as well as skilled labor. This paper proposes a smart and efficient technique for the detection of crop disease which uses computer vision and machine learning techniques. Every year India loses a significant amount of annual crop yield due to unidentified plant diseases. The traditional method of disease detection is manual examination by either farmers or experts, which may be time-consuming and inaccurate. It is proving infeasible for many small and medium-sized farms around the world. To mitigate this issue, a computer-aided disease recognition model is proposed. It uses leaf image classification with the help of deep convolutional networks. In this paper, CNN was proposed to detect plant disease. It has three processing steps namely feature extraction, downsizing image, and classification. In CNN, the convolutional layer extracts the feature from the plant image. It helps to give personalized recommendations to farmers based on soil features, temperature, and humidity.

Abstract-Human-centered artificial intelligence (HCAI) emphasizes designing AI systems that prioritize human values, ethics, and usability, fostering trust and responsible adoption. This research explores the advancement of HCAI by addressing key challenges such as improving explainability, integrating ethical considerations, and optimizing real-world applications across diverse sectors. By investigating state-of- the-art methods for interpretable machine learning, the study aims to enhance user understanding and transparency in AI decision-making. It further examines frameworks for embedding ethical principles, including fairness, accountability, and privacy, into AI system design. Additionally, the research evaluates case studies from healthcare, education, and autonomous systems to illustrate the transformative potential of HCAI. This study underscores the need for interdisciplinary collaboration and innovation to ensure AI technologies align with human values and societal goals, paving the way for more inclusive and sustainable AI solutions.